Microwave heating is an encouraging heating technology for the maintenance, recycling, and deicing of asphalt pavement. To investigate the microwave heating properties of asphalt mixture, laboratory tests and numerical simulations were done and compared. Two types of Stone Mastic Asphalt (SMA) mixture samples (with basalt aggregates and steel slag aggregates) were heated using a microwave oven for different times. Numerical simulation models of microwave heating of asphalt mixture were developed with finite element software COMSOL Multiphysics. The main thermal and electromagnetic properties of asphalt mixture, served as the model input parameters, were measured through a series of laboratory tests. Both laboratory-measured and numerical simulated surface temperatures were recorded and analyzed. Results show that the replacement of basalt aggregates with steel slag aggregates can significantly increase the microwave heating efficiency of asphalt mixture. Numerical simulation results have a good correlation with laboratory test results. It is feasible to use the developed model coupling electromagnetic waves with heat transfer to simulate the microwave heating process of asphalt mixture.

Pyrolytic carbon black (CB_p) from scrap tire pyrolysis is a potential modifier for the bitumen industry. Binders containing different contents of CB_p were prepared and experimentally investigated to examine the effects of CB_p on the electrical and thermal conductivity, conventional physical properties, rheological properties, high-temperature antirutting performance, aging resistance, and storage stability. Laboratory test results indicated that the incorporation of CB_p effectively improves the electrothermal properties, rheological properties, high-temperature rutting resistance, and aging resistance. It also increases the viscosity and decreases the storage stability of bitumen. The study confirms that CB_p-modified bitumen with proper selection of content can be a multifunctional paving material.

This note presents some constant-head permeability test results on 30 granular mixtures. These data are then interpreted using the grading entropy approach, as well as the ‘Hazen’, ‘Shepherd’, ‘Kozeny–Carman’ and ‘Chapuis’ models. The predictive power of each of the five methods is compared. A correlation between the normalised grading entropy coordinates and the coefficient of permeability is presented. Permeability zones on the normalised entropy diagram are identified.

Saturated hydraulic conductivity is a key soil mechanics parameter which has widespread use in many geotechnical applications. In order to set up stochastic analyses, geotechnical modellers require databases to calibrate the parameter ranges and distributions employed. This letter uses a recently compiled database of saturated hydraulic conductivity measurements called FG/KSAT-1358 and reports on the fitting of various probability density functions to the data of void ratio, liquid limit, water content ratio and the negative natural logarithm of k_sat. It is shown that the best fit distribution is the lognormal for void ratio, while the loglogistic distribution is most favoured for liquid limit and water content ratio, and the best fit distribution for -ln[k_sat(m/s)] is the logistic function. The data of -ln[k_sat(m/s)] is then subdivided according to liquid limit level, silt or clay classification, type of hydraulic conductivity test used and sample preparation/condition. When some subdivisions of the database are analysed, the best fit distribution is more variable with GEV and logistic being the most favoured for most of the studied subsets.